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Hybrid Systems for Personalized Recommendations

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Intelligent Techniques for Web Personalization (ITWP 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3169))

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Abstract

A variety of techniques have been proposed and investigated for delivering personalized recommendations for electronic commerce and other web applications. To improve performance, these methods have sometimes been combined in hybrid recommenders. This chapter surveys the landscape of actual and possible hybrid recommenders, and summarizes experiments that compare a large set of hybrid recommendation designs.

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Author information

Authors and Affiliations

  1. School of Computer Science, Telecommunications and Information Systems, DePaul University, 243 S. Wabash Ave., Chicago, Illinois

    Robin Burke

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  1. Robin Burke
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Editor information

Editors and Affiliations

  1. Center for Web Intelligence School of Computing, DePaul University, Chicago, Illinois, USA

    Bamshad Mobasher

  2. Department of Computer Science, University of Warwick, Coventry, United Kingdom

    Sarabjot Singh Anand

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© 2005 Springer-Verlag Berlin Heidelberg

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Burke, R. (2005). Hybrid Systems for Personalized Recommendations. In: Mobasher, B., Anand, S.S. (eds) Intelligent Techniques for Web Personalization. ITWP 2003. Lecture Notes in Computer Science(), vol 3169. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11577935_7

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  • DOI: https://doi.org/10.1007/11577935_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29846-5

  • Online ISBN: 978-3-540-31655-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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